Pickl AI

AUGUST 9, 2024

Some of the most notable technologies include: Hadoop An open-source framework that allows for distributed storage and processing of large datasets across clusters of computers. It is built on the Hadoop Distributed File System (HDFS) and utilises MapReduce for data processing. Once data is collected, it needs to be stored efficiently.

Big Data 52

Big Data Big Data Big Data Analytics Big Data Analytics 52

ODSC - Open Data Science

OCTOBER 7, 2024

Techniques such as parallel data processing and distributed data storage systems, like Hadoop or cloud-native solutions, allow data scientists to ingest and store large volumes of data effectively. Building Scalable Data Pipelines The foundation of any AI pipeline is the data it consumes.

Machine Learning 52

Machine Learning Machine Learning AI AI 52

IBM Journey to AI blog

JULY 6, 2023

Today, machine learning has evolved to the point that engineers need to know applied mathematics, computer programming, statistical methods, probability concepts, data structure and other computer science fundamentals, and big data tools such as Hadoop and Hive. Python is the most common programming language used in machine learning.

Machine Learning 70

Machine Learning Machine Learning Data Science Big Data 70

Pickl AI

APRIL 28, 2023

Here is the tabular representation of the same: Technical Skills Non-technical Skills Programming Languages: Python, SQL, R Good written and oral communication Data Analysis: Pandas, Matplotlib, Numpy, Seaborn Ability to work in a team ML Algorithms: Regression Classification, Decision Trees, Regression Analysis Problem-solving capability Big Data: (..)

Data Scientist 52

Data Scientist Data Science Hypothesis Testing Decision Trees 52

Pickl AI

MAY 31, 2023

Begin by employing algorithms for supervised learning such as linear regression , logistic regression, decision trees, and support vector machines. It includes regression, classification, clustering, decision trees, and more. To obtain practical expertise, run the algorithms on datasets.

Data Science 52

Data Science Python Data Scientist Machine Learning 52

Pickl AI

JULY 18, 2023

With its powerful ecosystem and libraries like Apache Hadoop and Apache Spark, Java provides the tools necessary for distributed computing and parallel processing. It is helpful in descriptive and inferential statistics, regression analysis, clustering, decision trees, neural networks, and more.

Data Science 52

Data Science SQL Data Scientist Python 52

Pickl AI

NOVEMBER 28, 2024

Decision Trees These trees split data into branches based on feature values, providing clear decision rules. Big Data Tools Integration Big data tools like Apache Spark and Hadoop are vital for managing and processing massive datasets. It’s simple but effective for many problems like predicting house prices.

Machine Learning 52

Machine Learning Machine Learning ML ML 52

Pickl AI

JULY 10, 2023

Packages like dplyr, data.table, and sparklyr enable efficient data processing on big data platforms such as Apache Hadoop and Apache Spark. . · Big Data Analytics: R has solutions for handling large-scale datasets and performing distributed computing. Suppose you want to develop a classification model to predict customer churn.

Data Science 52

Data Science Data Scientist Machine Learning Machine Learning 52

ODSC - Open Data Science

JANUARY 7, 2025

Hadoop, though less common in new projects, is still crucial for batch processing and distributed storage in large-scale environments. Classification techniques like random forests, decision trees, and support vector machines are among the most widely used, enabling tasks such as categorizing data and building predictive models.

Data Scientist 40

Data Scientist Data Science Machine Learning Machine Learning 40

Pickl AI

DECEMBER 4, 2024

Dive Deep into Machine Learning and AI Technologies Study core Machine Learning concepts, including algorithms like linear regression and decision trees. Gain Experience with Big Data Technologies With the rise of Big Data, familiarity with technologies like Hadoop and Spark is essential.

Data Science 52

Data Science Data Scientist Machine Learning Machine Learning 52